To minimize user interface we sought to develop a filtering algorithm in the post processing and compared automated AUC detection with operator directed AUC assessment... A time-intensity curve was generated by tracing and plotting the blood signals in the left atrium including all image phases and processed in a custom Matlab program with and without the filtering algorithm... The unfiltered and filtered AUC were compared to the operator directed assessment... The example in Figure 1 shows a time-intensity curve from unfiltered data... Without filtering the AUC ended at phase 52 due to an artifact, while a filtered program detected AUC up to phase 60 which coincided with the AUC assessed by an experienced operator... Of the 37 cases analyzed, artifacts were present in 18 cases... The filtering algorithm was successful at detecting and removing artifacts in all 18 cases... As a result, the filtered AUC was much closer to the operator directed AUC shown (in green and in red, respectively) in Figure 2 than unfiltered AUC (in blue) was... Bland-Altman analysis demonstrated a much improved agreement between filtered and operator directed AUC detection (Figure 4) than filtered and unfiltered AUC (Figure 3)... Artifact is common in time-intensity curve of the LA blood signal.

Mentions:
Of the 37 cases analyzed, artifacts were present in 18 cases. The filtering algorithm was successful at detecting and removing artifacts in all 18 cases. As a result, the filtered AUC was much closer to the operator directed AUC shown (in green and in red, respectively) in Figure 2 than unfiltered AUC (in blue) was. Bland-Altman analysis demonstrated a much improved agreement between filtered and operator directed AUC detection (Figure 4) than filtered and unfiltered AUC (Figure 3).

Mentions:
Of the 37 cases analyzed, artifacts were present in 18 cases. The filtering algorithm was successful at detecting and removing artifacts in all 18 cases. As a result, the filtered AUC was much closer to the operator directed AUC shown (in green and in red, respectively) in Figure 2 than unfiltered AUC (in blue) was. Bland-Altman analysis demonstrated a much improved agreement between filtered and operator directed AUC detection (Figure 4) than filtered and unfiltered AUC (Figure 3).

To minimize user interface we sought to develop a filtering algorithm in the post processing and compared automated AUC detection with operator directed AUC assessment... A time-intensity curve was generated by tracing and plotting the blood signals in the left atrium including all image phases and processed in a custom Matlab program with and without the filtering algorithm... The unfiltered and filtered AUC were compared to the operator directed assessment... The example in Figure 1 shows a time-intensity curve from unfiltered data... Without filtering the AUC ended at phase 52 due to an artifact, while a filtered program detected AUC up to phase 60 which coincided with the AUC assessed by an experienced operator... Of the 37 cases analyzed, artifacts were present in 18 cases... The filtering algorithm was successful at detecting and removing artifacts in all 18 cases... As a result, the filtered AUC was much closer to the operator directed AUC shown (in green and in red, respectively) in Figure 2 than unfiltered AUC (in blue) was... Bland-Altman analysis demonstrated a much improved agreement between filtered and operator directed AUC detection (Figure 4) than filtered and unfiltered AUC (Figure 3)... Artifact is common in time-intensity curve of the LA blood signal.